Host: The Japan Society of Mechanical Engineers
Name : [in Japanese]
Date : June 06, 2021 - June 08, 2021
We have developed a real-time binocular disparity detection system by combining the spatiotemporal properties of the visual nervous system and the binocular energy model. This system consists of two image sensors, three field-programmable gate arrays (FPGAs), a USB controller, and a personal computer (PC). The spatio-temporal properties implement motion direction selectivity into the binocular energy model, and can reduce the number of binocular matching candidates. We evaluated the system by presenting an object rotating at a constant angular velocity on a motor-controlled turntable to the system. While the original binocular energy model estimated a wrong disparity due to mismatching when the rotating object moved near a background object that has similar spatial features, the binocular disparity detection system estimated the correct disparity in the same situation because the spatio-temporal filter prevented the mismatching.
